Replicating cohesive and stress-history-dependent behavior of bulk solids

Replicating cohesive and stress-history-dependent behavior of bulk solids: Feasibility and definiteness in DEM calibration procedure

Mohajeri, M. (TU Delft Transport Engineering and Logistics)
van Rhee, C. (TU Delft Offshore and Dredging Engineering; TU Delft Rivers, Ports, Waterways and Dredging Engineering)
Schott, D.L. (TU Delft Transport Engineering and Logistics)

2021

This paper presents a multi-step DEM calibration procedure for cohesive solid materials, incorporating feasibility in finding a non-empty solution space and definiteness in capturing bulk responses independently of calibration targets. Our procedure follows four steps: (I) feasibility; (II) screening of DEM variables; (III) surrogate modeling-based optimization; and (IV) verification. Both types of input parameter, continuous (e.g. coefficient of static friction) and categorical (e.g. contact module), can be used in our calibration procedure. The cohesive and stress-history-dependent behavior of a moist iron ore sample is replicated using experimental data from four different laboratory tests, such as a ring shear test. This results in a high number of bulk responses (i.e. ≥ 4) as calibration targets in combination with a high number of significant DEM input variables (i.e. > 2) in the calibration procedure. Coefficient of static friction, surface energy, and particle shear modulus are found to be the most significant continuous variables for the simulated processes. The optimal DEM parameter set and its definiteness are verified using 20 different bulk response values. The multi-step optimization framework thus can be used to calibrate material models when both a high number of input variables (i.e. > 2) and a high number of calibration targets (i.e. ≥ 4) are involved.

Consolidation-penetration test
DEM calibration
Elasto-plastic adhesive contact spring
Ring shear test
Surrogate modeling-based optimization

http://resolver.tudelft.nl/uuid:a7420c9e-46a3-424d-ab34-ef66532ec621

https://doi.org/10.1016/j.apt.2021.02.044

0921-8831

Advanced Powder Technology, 32 (5), 1532-1548

Institutional Repository

journal article

© 2021 M. Mohajeri, C. van Rhee, D.L. Schott